Sensor selection for maneuver classification

Kari Torkkola, Srihari Venkatesan, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

To determine when to present information from various devices or services to the driver of an automobile, it is necessary to determine whether a driver is engaged in a difficult driving situation that requires extensive attention. We present simulator experiments in determining what sensors make classification of driving states into such maneuvers possible, using various machine learning techniques. Our findings indicate that a small number of derived sensor signals can accomplish the task.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Pages636-641
Number of pages6
StatePublished - 2004
EventProceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC 2004 - Washington, DC, United States
Duration: Oct 3 2004Oct 6 2004

Other

OtherProceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC 2004
CountryUnited States
CityWashington, DC
Period10/3/0410/6/04

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Torkkola, K., Venkatesan, S., & Liu, H. (2004). Sensor selection for maneuver classification. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 636-641)